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Adam D. Smith
I currently work as a Quantitative Ecologist with the United States Fish & Wildlife Service Inventory and Monitoring Program. I provide ecological and analytical assistance to the roughly 130 National Wildlife Refuges in 10 southeastern states.
I engage in diverse partnerships with conservation and resource management agencies and organizations to support a research program built around modern quantitative tools and approaches to understand the ecology and conservation of migratory animals. This integrative, multi-scale approach facilitates collaborative research relevant to conservation and management. I primarily use digitally-coded telemetry and GPS logging technology in landscape and local scale questions relative to anthropogenic influences. I am an open science advocate.
Education
PhD. Candidate, Biostatistics
Vanderbilt University
Nashville, TN
2020
- Working on Bayesian network models & interactive visualization platforms
- University Graduate Fellow
B.S., Mathematics, Statistics (minor C.S.)
University of Vermont
Burlington, VT
2015
- Thesis: An agent based model of Diel Vertical Migration patterns of Mysis diluviana
Professional Experience
Graduate Research Assistant
TBILab (Yaomin Xu’s Lab)
Vanderbilt University
2020 - 2015
- Primarily working with large EHR and Biobank datasets.
- Developing network-based methods to investigate and visualize clinically relevant patterns in data.
Data Science Researcher
Data Science Lab
Johns Hopkins University
2018 - 2017
- Building R Shiny applications in the contexts of wearables and statistics education.
- Work primarily done in R Shiny and Javascript (node and d3js).
Undergraduate Researcher
Rubenstein Ecosystems Science Laboratory
University of Vermont
2015 - 2013
- Analyzed and visualized data for CATOS fish tracking project.
- Head of data mining project to establish temporal trends in population densities of Mysis diluviana (Mysis).
- Ran project to mathematically model the migration patterns of Mysis (honors thesis project.)
Human Computer Interaction Researcher
LabInTheWild (Reineke Lab)
University of Michigan
2015
- Led development and implementation of interactive data visualizations to help users compare themselves to other demographics.
Undergraduate Researcher
Bentil Laboratory
University of Vermont
2014 - 2013
- Developed mathematical model to predict the transport of sulfur through the environment with applications in waste cleanup.
Research Assistant
Adair Laboratory
University of Vermont
2013 - 2012
- Independently analyzed and constructed statistical models for large data sets pertaining to carbon decomposition rates.
Publications
Charge Reductions Associated with Shortening Time to Recovery in Septic Shock
Chest
N/A
2019
- Authored with Wesley H. Self, MD MPH; Dandan Liu, PhD; Stephan Russ, MD, MPH; Michael J. Ward, MD, PhD, MBA; Nathan I. Shapiro, MD, MPH; Todd W. Rice, MD, MSc; Matthew W. Semler, MD, MSc.
Multimorbidity Explorer | A shiny app for exploring EHR and biobank data
RStudio::conf 2019
N/A
2019
- Contributed Poster. Authored with Yaomin Xu.
Taking a network view of EHR and Biobank data to find explainable multivariate patterns
Vanderbilt Biostatistics Seminar Series
N/A
2019
- University wide seminar series.
Patient-specific risk factors independently influence survival in Myelodysplastic Syndromes in an unbiased review of EHR records
Under-Review (copy available upon request.)
N/A
2019
- Bayesian network analysis used to find novel subgroups of patients with Myelodysplastic Syndromes (MDS).
- Analysis done using method built for my dissertation.
Patient specific comorbidities impact overall survival in myelofibrosis
Under-Review (copy available upon request.)
N/A
2019
- Bayesian network analysis used to find robust novel subgroups of patients with given genetic mutations.
- Analysis done using method built for my dissertation.
R timelineViz: Visualizing the distribution of study events in longitudinal studies
Under-Review (copy available upon request.)
N/A
2018
- Authored with Alex Sunderman of the Vanderbilt Department of Epidemiology.
Continuous Classification using Deep Neural Networks
Vanderbilt Biostatistics Qualification Exam
N/A
2017
- Review of methods for classifying continuous data streams using neural networks
- Successfully met qualifying examination standards
Asymmetric Linkage Disequilibrium: Tools for Dissecting Multiallelic LD
Journal of Human Immunology
N/A
2015
- Authored with Richard Single, Vanja Paunic, Mark Albrecht, and Martin Maiers.
An Agent Based Model of Mysis Migration
International Association of Great Lakes Research Conference
N/A
2015
- Authored with Brian O’Malley, Sture Hansson, and Jason Stockwell.
Declines of Mysis diluviana in the Great Lakes
Journal of Great Lakes Research
N/A
2015
- Authored with Peter Euclide and Jason Stockwell.
Presentations
Teaching Experience
Data Visualization Best Practices
DataCamp
N/A
2019
- Designed from bottom up course to teach best practices for scientific visualizations.
- Uses R and ggplot2.
- In top 10% on platform by popularity.
Improving your visualization in Python
DataCamp
N/A
2019
- Designed from bottom up course to teach advanced methods for enhancing visualization.
- Uses python, matplotlib, and seaborn.
Advanced Statistical Learning and Inference
Vanderbilt Biostatistics Department
Nashville, TN
2018 - 2017
- TA and lectured
- Topics covered from penalized regression to boosted trees and neural networks
- Highest level course offered in department
Advanced Statistical Computing
Vanderbilt Biostatistics Department
Nashville, TN
2018
- TA and lectured
- Covered modern statistical computing algorithms
- 4th year PhD level class
Statistical Computing in R
Vanderbilt Biostatistics Department
Nashville, TN
2017
- TA and lectured
- Covered introduction to R language for statistics applications
- Graduate level class